• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.3
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• pp.1-7
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• 2019

It is one of the known methods to obtain the optimal solution using the Ant Colony Optimization Algorithm for the Traveling Salesman Problem (TSP), which is a combination optimization problem. In this paper, we solve the TSP problem by proposing an improved new ant colony optimization algorithm that combines genetic algorithm mutations in existing ant colony optimization algorithms to solve TSP problems in many cities. The new ant colony optimization algorithm provides the opportunity to move easily fall on the issue of developing local optimum values of the existing ant colony optimization algorithm to global optimum value through a new path through mutation. The new path will update the pheromone through an ant colony optimization algorithm. The renewed new pheromone serves to derive the global optimal value from what could have fallen to the local optimal value. Experimental results show that the existing algorithms and the new algorithms are superior to those of existing algorithms in the search for optimum values of newly improved algorithms.

• Journal of Korea Multimedia Society
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• v.5 no.1
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• pp.114-119
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• 2002

Realtime assignment of railways is an important component in the railway control systems. To solve this problem, we must exactly represent the track topology. Graph is a proper data structure for representing general network topologies, but not Proper for track topologies. In this paper, we define a new data structure, railway graph, which can exactly represent topologies of railway networks. And we describe a path search algorithm in the defined railway graph, and a top-down approach for designing railway network by the Proposed graph.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.135-144
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• 2020

In graph theory, the least-cost path is discovered by searching the shortest path between a start node and destination node. The least cost is calculated as a one-dimensional value that represents the difference in distance or price between two nodes, and the nodes and edges that comprise the lowest sum of costs between the linked nodes is the shortest path. However, it is difficult to determine the shortest path if each node has multiple attributes because the number of cost types that can appear is equal to the number of attributes. In this paper, a shortest path search scheme is proposed that considers multiple attributes using the Euclidean distance to satisfy various user requirements. In simulation, we discovered that the shortest path calculated using one-dimensional values differs from that calculated using the Euclidean distance for two-dimensional attributes. The user's preferences are reflected in multi attributes and it was different from one-dimensional attribute. Consequently, user requirements could be satisfied simultaneously by considering multiple attributes.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.361-366
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• 2006

It is widely known that the dynamic optimal path algorithm, adopting real-time path finding, can be supporting an optimal route with which users are satisfied economically and accurately. However, this system has to search optimal routes frequently for updating them. The proposed concept of optimizing search area lets it reach heuristic optimal path rapidly and efficiently. Since optimal path should be increased in proportion to an distance between origin and destination, tremendous calculating time and highly efficient computers are required for searching long distance journey. In this paper, as a result of which the concepts of partial solution and representative path are suggested. It was possible to find an optimal route by decreasing a half area in comparison with the previous method. Furthermore, as the size of the searching area is uniform, comparatively low efficient computer is required for long distance trip.

• The Journal of the Korea Contents Association
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• v.7 no.1
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• pp.147-154
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• 2007

In this paper, we propose a new parallel search algorithm to acquire synchronization for UWB(Ultra Wideband) systems that reduces computation of the correlation. The conventional synchronization acquisition algorithms check all the possible signal phases simultaneously using multiple correlators. However it reduces the acquisition time, it makes high power consumption owing to increasing of correlation. The proposed algorithm divides the preamble signal to input the correlator into an m-bit bunch. We check the result of the correlation at first stage of an m-bit bunch data and predict whether it has some synchronization acquisition information or not. Thus, it eliminates the unnecessary operation and save the number of correlation. We evaluate the proposed algorithm under the AWGN and the multi-Path channel model with MATLAB. The proposed parallel search scheme reduces number of the correlation 65% on the AWGN and 20% on the multi-path fading channel.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.654-662
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• 2016

As the number of gates and basic events in fault trees increases, it becomes difficult to calculate the exact probability of the top event. In order to overcome this difficulty the BDD methodology can be used to calculate the exact top event probability for small and medium size fault trees in short time. Fault trees are converted to BDD by using CUDD library functions and a failure path search algorithm is proposed to calculate the exact top event probability. The backward search algorithm is more efficient than the forward one in finding failure paths and in the calculation of the top event probability. This backward search algorithm can reduce searching time in the identification of disjoint failure paths from BDD and can be considered as an effective tool to find the cut sets and the minimal cut sets for the given fault trees.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.3-9
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• 2015

Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.6
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• pp.385-392
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• 2022

Naval ship could face a variety of threats in isolated seas. In particular, fires and flooding are defined as disasters that are very likely to cause irreparable damage to ships. These disasters have a very high risk of personal injury as well. Therefore, when a disaster occurs, it must be quickly suppressed, but if there are people in the disaster area, the protection of life must be given priority. In order to quickly evacuate the ship crew in case of a disaster, we would like to propose a plan to quickly explore the evacuation route even in urgent situations. Using commercial escape simulation software, we obtain the data for deep neural network learning with simulations according to aisle characteristics and the properties and number of evacuation person. Using the obtained data, the passage prediction model is trained with a deep learning, and the passage time is predicted through the learned model. Construct a numerical map of a naval ship and construct a distance matrix of the vessel using predicted passage time data. The distance matrix configured in one of the path search algorithms, the Dijkstra algorithm, is applied to explore the evacuation path of naval ship.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.141-150
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• 2012

This paper suggests a critical path search algorithm that can easily draw PERT/GANTT chart which manages and plans a project schedule. In order to evaluate a critical path that determines the project schedule, Critical Path Method (CPM) is generally utilized. However, CPM undergoes 5 stages to calculate the critical path for a network diagram that is previously designed according to correlative relationship and execution period of project execution activities. And it may not correctly evaluate $T_E$ (The Earliest Time), since it does not suggest the way how to determine the sequence of the nodes activities that calculate the $T_E$. Also, the sequence of the network diagram activities obtained from CPM cannot be visually represented, and hence Lucko suggested an algorithm which undergoes 9 stages. On the other hand, the suggested algorithm, first of all, decides the sequence in advance, by reallocating the nodes into levels after Breadth-First Search of the network diagram that is previously designed. Next, it randomly chooses nodes of each level and immediately determines the critical path only after calculation of $T_E$. Finally, it enables the representation of the execution sequence of the project activity to be seen precisely visual by means of a small movement of $T_E$ of the nodes that are not belonging to the critical path, on basis of the $T_E$ of the nodes which belong to the critical path. The suggested algorithm has been proved its applicability to 10 real project data. It is able to get the critical path from all the projects, and precisely and visually represented the execution sequence of the activities. Also, this has advantages of, firstly, reducing 5 stages of CPM into 1, simplifying Lucko's 9 stages into 2 stages that are used to clearly express the execution sequence of the activities, and directly converting the representation into PERT/GANTT chart.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.85-92
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• 2015

As computer game maps get more elaborate, path-finding by using $A^*$ algorithm in grid-based game maps becomes bottlenecks of the overall game performance. It is because the search space becomes large as the number of nodes increases with detailed representation in cells. In this paper we propose an efficient pathfinding method in which the computer game maps in a regular grid is converted into the polygon-based representation of the list of vertices and then the visibility information about vertices of polygons can be utilized. The conversion to the polygon-based map does not give any effect to the real-time query process because it is preprocessed offline. The number of visited nodes during search can be reduced dramatically by designing heuristics using visibility information of vertices that make the accuracy of the estimation enhanced. Through simulations, we show that the proposed methods reduce the search space and the search time effectively while maintaining the advantages of the grid-based method.